How does Big Data work?

Posted by KingEclient on 6 April, 2016

The information we obtain from our digital devices today is of great value and is capable of changing almost everything we do, especially in marketing. Eric Schmidt, CEO of Google, maintains that we now generate more information in just two days than in the entire history of mankind up to 2003.

Big Data technology can be difficult to grasp for anyone not working in data analysis. Our intention in this post is to sum up the way it works for those who may wish to start using it in their marketing strategies. We will start by explaining the three concepts which are known as the three “V”s:

Variety: the wider the range of sources of information, the easier it is to expand the market, find new users and locate new market segments.

Volume: the strategies for filtering the necessary information need to be appropriately aligned in order to deal with the vast amount of information generated.

Velocity: Big Data is able to provide information in real time, which is a considerable advantage, as the mission of marketing professionals is to respond instantly to changing circumstances and to be able to adapt their approach to customer behaviour.

In line with these three ideas, Toni Martí Barberá, an acknowledged expert in Marketing Directo, defines Big Data as the capacity to gather massive, varied and rapidly changing volumes of data, to structure it and finally to prepare it for analysis.

Regardless of the sector in which they are working, companies can find information about users from the following sources.

Web analytics: This provides us with the point of view of the web browser, not the user. Data is usually collected from cookies on a classic website, mobile websites, apps, blogs, etc.

Adverser: Like web analytics, the use of cookies gives us the point of view of the web browser. This method collects information on the impact of advertising on online users and stores both the number of impressions and the number of clicks made during different advertising campaigns.

Offline: There are a number of databases which collect all kinds of information on customers. Many companies have more than five separate databases but they are not always well structured. For example, retail databases may collect information both on sales and on customers, but the chances are that they are not linked.

It is necessary to manage offline data efficiently in order to get the most out of it. One needs to decide in advance what data to select and how to structure it. Only when those parameters are set can one start to select data and finally implement new measures based on any new insights.

But, says Clemares, for Big Data to provide a competitive edge, the company has to organize itself appropriately to deal with the information (know who owns it, where it is found…), to identify the technology to be used, and lastly, to employ business analysts, data scientists and statisticians to work on the data.

Companies who wish to incorporate Big Data have to face the costs and deal with the need to identify applications which will gain added value from it. According to the OBS study Big Data 2015 there are an increasing number of companies using this approach. In 2014 73% of world organizations were planning to invest in Big Data over the following two years; at the same time the number of companies not planning to incorporate this technology had dropped from 31% to 24%.

North America is the region with the highest number of companies using Big Data, with some 47% of companies using this technology. What is more, a massive 30 billion devices are expected to be connected to the internet by 2020, so Big Data will be ever more necessary for company growth.

So what about your company? Have you are already implemented this kind of strategy? Please feel free to leave your comments.